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https://github.com/torch-js/torch-js

Node.js binding for PyTorch.
https://github.com/torch-js/torch-js

nodejs pytorch

Last synced: 3 months ago
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Node.js binding for PyTorch.

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README 

        
# TorchJS



TorchJS is a JS binding for PyTorch. Its primary objective is to allow running [Torch Script](https://pytorch.org/docs/master/jit.html) inside Node.js program. Complete binding of libtorch is possible but is out-of-scope at the moment.



## Example



In `test/torch_module.py`, you will find the defination of our test module and the code to generate the trace file.



```python

class TestModule(torch.nn.Module):

    def __init__(self):

        super(TestModule, self).__init__()



    def forward(self, input1, input2):

        return input1 + input2

```



Once you have the trace file, you can load it into Node.js like this



```javascript

const torch = require("torch-js");



var test_model_path = "test/test_model.pt";



var script_module = new torch.ScriptModule(test_model_path);

console.log(script_module.toString());



var a = torch.rand(1, 5);

console.log(a.toObject());

var b = torch.rand([1, 5]);

console.log(b.toObject());



var c = script_module.forward(a, b);

console.log(c.toObject());



var d = torch.tensor([[0.1, 0.2, 0.3, 0.4, 0.5]]);

console.log(d.toObject());



var e = script_module.forward(c, d);

console.log(e.toObject());

```



The program above will print something like this on console. Your result will be different from this since `a` and `b` are random variables.



```javascript

ScriptModule("/Users/kittipat/torchjs/tests/test_model.pt")

{ data:

   Float32Array [

     0.5436246991157532,

     0.30234378576278687,

     0.4031236171722412,

     0.8123507499694824,

     0.3121740221977234 ],

  shape: [ 1, 5 ] }

{ data:

   Float32Array [

     0.20072013139724731,

     0.09114563465118408,

     0.588677167892456,

     0.14665216207504272,

     0.8567551374435425 ],

  shape: [ 1, 5 ] }

{ data:

   Float32Array [

     0.7443448305130005,

     0.39348942041397095,

     0.9918007850646973,

     0.9590029120445251,

     1.168929100036621 ],

  shape: [ 1, 5 ] }

{ data:

   Float32Array [

     0.10000000149011612,

     0.20000000298023224,

     0.30000001192092896,

     0.4000000059604645,

     0.5 ],

  shape: [ 1, 5 ] }

{ data:

   Float32Array [

     0.8443448543548584,

     0.593489408493042,

     1.2918007373809814,

     1.359002947807312,

     1.668929100036621 ],

  shape: [ 1, 5 ] }

```



### Tensor creation



There are several ways to create tensors



```javascript

// With TypedArray and shape array

var a = torch.tensor(

  new Float32Array([0.1, 0.2, 0.3, 0.4, 0.5]), {

    shape: [1, 5],

  });



// With array, will create tensor with float32 data type

var b = torch.tensor([

  [0.1, 0.2, 0.3],

  [0.4, 0.5, 0.6],

]);



// With array and option object

var c = torch.tensor([

  [0.1, 0.2, 0.3],

  [0.4, 0.5, 0.6],

], {

  dtype: torch.float64

});



// With torch.Tensor.fromObject()

var d = torch.Tensor.fromObject({

  data: new Float32Array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6]),

  shape: [2, 3],

});

```



## Installation



This project uses `cmake-js` to build Node extension. You will need to download [the preview build of libtorch](https://pytorch.org/get-started/locally/) and extract it to an accessible location. The build script assumes you put `libtorch` in the same directory as this library. E.g., if you checked out this library to `~/torch-js`, then `libtorch` should be at `~/libtorch`. Once you have that, you can run



```bash

yarn install

```



And, to test, run:



```bash

node tests/runTorch.js

```



If it failed to run because `libmklml` is missing, you can download it from conda.



```bash

conda install libmklml

```



If conda's `lib` directory is in your path, then you should be able to run the command above. Otherwise, you can set environment variable to point to the directory.



On macOS, it would be:



```bash

DYLD_LIBRARY_PATH=$CONDA_PREFIX/lib/ node tests/runTorch.js

```



On Linux, it should be:



```bash

LD_LIBRARY_PATH=$CONDA_PREFIX/lib/ node tests/runTorch.js

```



If there is any error loading the trace file, you might have to resolve it by installing the matching versions of PyTorch and libtorch and regenerate the file.